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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22

Multimodal X-ray nano-spectromicroscopy analysis of chemically heterogeneous systems

Abstract Understanding the nanoscale chemical speciation of heterogeneous systems in their native environment is critical for several disciplines such as life and environmental sciences, biogeochemistry, and materials science. Synchrotron-based X-ray spectromicroscopy tools are widely used to understand the chemistry and morphology of complex material systems owing to their high penetration depth and sensitivity. The multidimensional (4D+) structure of spectromicroscopy data poses visualization and data-reduction challenges. This paper reports the strategies for the visualization and analysis of spectromicroscopy data. We created a new graphical user interface and data analysis platform named XMIDAS (X-ray multimodal image data analysis software) to visualize spectromicroscopy data from both image and spectrum representations. The interactive data analysis toolkit combined conventional analysis methods with well-established machine learning classification algorithms (e.g. nonnegative matrix factorization) for data reduction. The data visualization and analysis methodologies were then defined and optimized using a model particle aggregate with known chemical composition. Nanoprobe-based X-ray fluorescence (nano-XRF) and X-ray absorption near edge structure (nano-XANES) spectromicroscopy techniques were used to probe elemental and chemical state information of the aggregate sample. We illustrated the complete chemical speciation methodology of the model particle by using XMIDAS. Next, we demonstrated the application of this approach in detecting and characterizing nanoparticles associated with alveolar macrophages. Our multimodal approach combining nano-XRF, nano-XANES, and differential phase-contrast imaging efficiently visualizes the chemistry of localized nanostructure with the morphology. We believe that the optimized data-reduction strategies and tool development will facilitate the analysis of complex biological and environmental samples using X-ray spectromicroscopy techniques.

36 MATERIALS SCIENCE↗

Evaluation of Composite Structural Materials for Heliostat Cost Reduction

Structures manufactured from steel comprise up to 40% of a CSP heliostat's cost. Composite structures represent a potential opportunity to reduce this cost. A reference heliostat structural model has been created with a reflector area of 25m 2 . The design, constructed of low-carbon steel, pro-vides baseline deflection and stiffness under a 21 m/s operating wind speeds. Wind loads on the tracker structure are determined for both operating and stow conditions. An established roster of suitable metal alternative materials is considered including: glass, basalt, and carbon reinforced polymer (GFRP, BFRP, and CFRP respectively). Three heliostat components are investigated: the pylon, torque tube, and the purlin-strut assembly. Composite material properties are substituted for those of steel, and the beams are re-sized to match the original steel components' deflection under given wind loads. Weight and cost changes resulting from this resizing are evaluated. It is found that GFRP and BFRP represent a 3X–6X cost premium for the same operating deflection character-istics as steel across all three investigated component classes; with weight reduction only achieved for the purlin-strut assembly. While CFRP components can achieve approximately 25–75% weight savings depending on the application, this comes with a 9X–14X cost increase over the steel base-line for tube-type structures and roughly 5X cost increase when replacing c-channel structures. This work does not rule out the possibility of cost savings when the heliostat design and kinematics to take advantage of composites' specific properties.

14 SOLAR ENERGY↗

MBIR: A cryo-ET 3D reconstruction method that effectively minimizes missing wedge artifacts and restores missing information

Cryo-Electron Tomography (cryo-ET) has become an essential technique in revealing cellular and macromolecular assembly structures in their native states. However, due to radiation damage and the limited tilt range, cryo-ET suffers from low contrast and missing wedge artifacts, which limits the tomograms to low resolution and hinders further biological interpretation. We applied the Model-Based Iterative Reconstruction (MBIR) method to obtain tomographic 3D reconstructions of experimental cryo-ET datasets and demonstrated the advantages of MBIR in contrast improvement, missing wedge artifacts reduction, missing information restoration, and subtomogram averaging compared with other reconstruction approaches. Considering the outstanding reconstruction quality, MBIR has a great potential in the determination of high resolution biological structures with cryo-ET.

59 BASIC BIOLOGICAL SCIENCES↗

KRAS interaction with RAF1 RAS-binding domain and cysteine-rich domain provides insights into RAS-mediated RAF activation

The first step of RAF activation involves binding to active RAS, resulting in the recruitment of RAF to the plasma membrane. To understand the molecular details of RAS-RAF interaction, we present crystal structures of wild-type and oncogenic mutants of KRAS complexed with the RAS-binding domain (RBD) and the membrane-interacting cysteine-rich domain (CRD) from the N-terminal regulatory region of RAF1. Our structures reveal that RBD and CRD interact with each other to form one structural entity in which both RBD and CRD interact extensively with KRAS. Mutations at the KRAS-CRD interface result in a significant reduction in RAF1 activation despite only a modest decrease in binding affinity. Combining our structures and published data, we provide a model of RAS-RAF complexation at the membrane, and molecular insights into RAS-RAF interaction during the process of RAS-mediated RAF activation.

60 APPLIED LIFE SCIENCES↗

Viscoelastic Material Characterization and Modeling of Photovoltaic Module Packaging Materials for Direct Finite-Element Method Input

Numerical tools, such as the finite-element method, are increasingly used to design and evaluate the photovoltaic (PV) modules, providing for the reduction of development time and improved performance and reliability. However, high-fidelity material models are necessary to accurately model the complex structural behavior of the involved packaging materials. A common simplification used in recent years is to model the polymer materials (i.e., encapsulant and backsheet) as linear elastic, which will lead to inaccurate results. Therefore, in this work, we present a thorough characterization of the time- and temperature-dependent mechanical response of predominant PV module encapsulant and backsheet materials. Based on this material characterization, we developed and experimentally validated generalized Maxwell models to describe each material's viscoelastic response. In addition, we included measurements of the coefficient of thermal expansion and presented all material models in such a fashion for direct input into commercial finite-element method modeling software.

FEM↗

DEMONSTRATION OF TWICE REDUCED LORENTZ FORCE DETUNING IN SRF CAVITY BY COPPER COLD SPRAYING

Superconducting RF (SRF) cavities usually are made of thin-wall high RRR Niobium that is susceptible to Lorentz Force Detuning (LFD) ? cavity deformation phenomena caused by high magnitude RF fields. This type of deformation can be mitigated by using an additional copper layer deposited on the outer surface of the cavity. In this paper, we present both modeling results and experimental data of high gradient test of an SRF cavity at cryogenic temperatures. It was demonstrated that LFD can be significantly reduced (factor of two) by the copper cold spray reinforcement without sacrificing cavity flexibility for tuning. We also present a finite-element model that allows us to confirm our experimental results and optimize the cavity geometry for LFD reduction with incorporated coupled RF, structural and thermal modules.

Kostin, R.↗

Advanced Geomechanical Model to Predict the Impact of CO2-Induced Microstructural Alterations on the Cohesive-Frictional Behavior of Mt. Simon Sandstone

We investigated the influence of CO2-induced geochemical reactions on the cohesive-frictional properties of host rock within the context of CO2 storage in a saline aquifer and focused on the Mt. Simon sandstone. The research objective was to model geo-mechanical changes due to host rock exposure to CO2-saturated brine while accounting for heterogeneity, double-scale porosity, and granular structure. We formulated a three-level multi-scale model for host rocks. We conducted scanning electron microscopy analyses to probe the microstructure and grid nanoindentation to measure the mechanical response. We derived new nonlinear strength upscaling solutions to correlate the effective strength characteristics and the macroscopic yield surface to the micro-structure at the nano-, micro-, and meso-scales. Specifically, our theoretical model links CO2-induced microstructural alterations to a reduction in the size of the yield surface, and a drop in the value of the friction coefficient. In turn, regarding the Illinois Basin Decatur Project, the CO2-induced drop in friction coefficient is linked to an increase in the risk of fault slip and a higher probability of induced microseismicity during and after the end of CO2 underground injection operations. The theoretical model presented is essential for the geo-mechanical modeling of CO2 underground injection operations at multiple length-scales.

58 GEOSCIENCES↗

A nonlinear structural concept for compliant walls

Two mechanisms of drag reduction for flow over flat plates were investigated. The first mechanism employs Bushnell's hypothesis that compliant walls produce drag reduction by interfering with the formation of the turbulent spots in a turbulent boundary layer. It is shown that the amplitudes and frequencies of compliant wall motions for drag reduction might be achieved by using slightly curved walls and the resulting large amplitude motions of snap buckling. A simple structural model of an arch is used in the analysis, and an asymptotic method is developed. The required wall motions can be obtained by using materials like mylar. In addition, the delay of transition from laminar to turbulent flow by driven walls was studied for Poiseuille channel flow. The walls are driven by a periodic traveling wave. A significant increase in the transitional Reynolds number is obtained by appropriately prescibing the wavelength and phase velocity of the wall motion. Previously developed asymptotic methods are used in the analysis.

Reiss, E. L.↗

A nonlinear structural concept for drag-reducing compliant walls

Two mechanisms of drag reduction for flow over flat plates were investigated. The first mechanism employs Bushnell's hypothesis that compliant walls produce drag reduction by interfering with the formation of the turbulent spots in a turbulent boundary layer. It is shown that the amplitudes and frequencies of compliant wall motions for drag reduction might be achieved by using slightly curved walls and the resulting large amplitude motions of snap buckling. A simple structural model of an arch is used in the analysis, and an asymptotic method is developed. The required wall motions can be obtained by using materials like mylar. In addition, the delay of transition from laminar to turbulent flow by driven walls was studied for Poiseuille channel flow. The walls are driven by a periodic traveling wave. A significant increase in the transitional Reynolds number is obtained by appropriately prescribing the wavelength and phase velocity of the wall motion. Previously developed asymptotic methods are used in the analysis. Previously announced in STAR as N83-11061

Reiss, E. L.↗

Residue-Measure Model-Reduction Technique

New residue-measure criterion simplifies mathematical models of feedback-control systems. Although originally developed for flight control, approach applied to any flexible structural system involving dominantly linear dynamics.

Gluch, D. P.↗

Machine Learning for Dynamic Test Sensor Placement

There are multiple different algorithms to perform modal test sensor placement optimization: effective independence, residual kinetic energy, iterative Guyan reduction, genetic algorithms, or a brute-force methodology. However, any of these methods may be computationally expensive, especially for structural models with a large number of degrees of freedom. Given the high-cost and the need to optimize the solution, modal sensor placement is a great application for machine learning (ML) algorithms. In this paper, we will apply ML algorithms to determine the optimal sensor locations for simple and complex structures. We will also discuss the benefits and drawbacks of using machine learning over other sensor placement algorithms.

Kelsey Buckles↗

Experimental and kinetic analysis for particle scale modeling of a CuO-Fe 2 O 3 -Al 2 O 3 oxygen carrier during reduction with H 2 in chemical looping combustion applications [Experimental and kinetic analysis for particle scale modeling of a CuO-Fe 2 O 3 -Al 2 O 3 oxygen carrier during reduction with CO in chemical looping combustion applications]

A kinetic analysis of the H 2 reduction of a CuO-Fe 2 O 3 -Al 2 O 3 oxygen carrier in gas phase fueled Chemical Looping Combustion of synthesis gas was utilized to derive particle scale representation. An experimentally driven study was carried out to provide an array of operational data sets for kinetic modelling approaches. The impact of key operational variables on the kinetics of the novel oxygen carrier were examined, with emphasis on the application of reliable phenomena driven particle scale models to describe the reduction behavior. Due to the novel nature of the material, a series of experimental studies were carried out to provide a fundamental understanding of how the material changed as oxygen was depleted from the structure due to reduction with H 2 . This include quantification of the complex mixed metal oxide phase and changes due to lattice oxygen depletion. It was found that H 2 reduction occurs in a multistep process where CuFeAlO 4 → Cu 0+ + FeAl 2 O 4 → Cu 0+ + Fe 0+ + Al 2 O 3 as oxygen is depleted from the structure. This multistep process was successfully emulated through the use of a two interface Grainy pellet model in which reaction (kinetic) control was the main rate limiting step. This is validated through the examination of other potential rate limiting resistances. In conclusion, the model emulates changes in key operation variables with good accuracy.

42 ENGINEERING↗

Tricoupled hybrid lattice Boltzmann model for nonisothermal drying of colloidal suspensions in micropore structures

A tricoupled hybrid lattice Boltzmann model (LBM) is developed to simulate colloidal liquid evaporation and colloidal particle deposition during the nonisothermal drying of colloidal suspensions in micropore structures. An entropic multiple-relaxation-time multirange pseudopotential two-phase LBM for isothermal interfacial flow is first coupled to an extended temperature equation for simulating nonisothermal liquid drying. Then the coupled model is further coupled with a modified convection diffusion equation to consider the nonisothermal drying of colloidal suspensions. Two drying examples are considered. First, drying of colloidal suspensions in a two-pillar micropore structure is simulated in two dimensions (2D), and the final configuration of colloidal particles is compared with the experimental one. Good agreement is observed. Second, at the temperature of 343.15 K ( 70°C ), drying of colloidal suspensions in a complex spiral-shaped micropore structure containing 220 pillars is simulated (also in 2D). The drying pattern follows the designed spiral shape due to capillary pumping, i.e., transport of the liquid from larger pores to smaller ones by capillary pressure difference. Because the colloidal particles are passively carried with liquid, they accumulate at the small menisci as drying proceeds. As liquid evaporates at the small menisci, colloidal particles are deposited, eventually forming solid structures between the pillars (primarily), and at the base of the pillars (secondarily). As a result, the particle deposition conforms to the spiral route. Qualitatively, the simulated liquid and particle configurations agree well with the experimental ones during the entire drying process. Quantitatively, the model demonstrates that the evaporation rate and the particle accumulation rate slowly decrease during drying, similar to what is seen in the experimental results, which is due to the reduction of the liquid-vapor interfacial area. In conclusion, the hybrid model shows the capability and accuracy for simulating nonisothermal drying of colloidal suspensions in a complex micropore structure both qualitatively and quantitatively, as it includes all the required physics and captures all the complex features observed experimentally. Such a tricoupled LBM has a high potential to become an efficient numerical tool for further investigation of real and complex engineering problems incorporating drying of colloidal suspensions in porous media.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Distributed parameter modeling for the control of flexible spacecraft

The use of FEMs of spacecraft structural dynamics is a common practice, but it has a number of shortcomings. Distributed-parameter models offer an alternative, but present both advantages and difficulties. First, the model order does not have to be reduced prior to the inclusion of control system dynamics. This advantage eliminates the risk involved with model 'order reduction'. Second, distributed parameter models inherently involve fewer parameters, thereby enabling more accurate parameter estimation using experimental data. Third, it is possible to include the damping in the basic model, thereby increasing the accuracy of the structural damping. The difficulty in generating distributed parameter models of complex spacecraft configurations has been greatly alleviated by the use of PDEMOD, BUNVIS-RG, or DISTEL. PDEMOD is being developed for simultaneously modeling structural dynamics and control system dynamics.

Taylor, Lawrence W., Jr.↗

Universal Solvent Viscosity Reduction via Hydrogen Bonding Disruptors

Liquid Ion Solutions LLC (DBA RoCo Global) in partnership with Carnegie Mellon University and Carbon Capture Scientific LLC, has performed lab-scale development and evaluation of novel additives that lower the viscosity of water-lean amine solvents for post-combustion carbon dioxide capture. This project focuses on developing additives that minimize the formation of long-range electrostatic and hydrogen bonding (HB) networks, decreasing the solvent viscosity, improving diffusion, and improving the process economics. The project objectives included: 1) performing computer simulation to understand the molecular interactions of the additive molecules in water-lean CO 2 capture solvents, 2) design and synthesis of HB disruptors additives, 3) performance testing with additive molecules on model amine solvents, and 4) demonstration of the effectiveness of the optimized additives in the presence of synthetic flue gas. To meet the abovementioned objectives, the project team utilized a holistic approach that combines molecular simulation, experimental testing, and economic analysis studies. The project team developed ab initio molecular model and then perform computer simulation to develop relationship between hydrogen bonding, viscosity, and performed quantitative analysis of additive on the viscosity of the solvent. The team completed computational comparative study on a range of organic functional groups such as ethers, esters, cyclic carbonates, alkanes, and ammonium salts for their effect on viscosity gaining key insights into molecular interactions and the impact of various functional groups and molecular shapes on viscosity. Assisted with molecular simulation insights, the project team conducted additive synthesis and testing, including a proof-of-concept study, additive screening, optimization, and synthetic flue gas testing. The experimental proof-of-concept study proved that the hydrogen bonding acceptors result in significant decrease of viscosities. Detailed additive screening (exploring various functionalities and molecular structures) has been performed. Several promising additives showed excellent reduction in viscosity (30-41%) at 5% additive loading, and over 50% viscosity reduction at 10% additive loading for the model solvents. The team also performed complex screening studies on additive loadings and mixing effect among additives using the design of experiments. Based on multiple screening experiments, one additive-solvent candidate was down-selected for synthetic flue gas testing. A 100-hour continuous absorption/desorption study was conducted under simulated flue gas using a lab-scale continuous capture and separation system. No degradation (for both solvent and additive) was observed based on the GC results of the solvent samples collected from the continuous study. The team conducted preliminary engineering analyses and cost-benefit analyses to quantify the potential economic benefits of the additive approach for solvent viscosity reduction. Based on the experimental data, CO 2 capture cost savings from the capital and operating cost savings are estimated at $\$$4.7/tonne and $\$$0.3/tonne CO 2 captured, respectively. Considering the additive cost, the net benefit is estimated to be between $\$$4.32~$\$$4.86/tonne CO 2 captured.

20 FOSSIL-FUELED POWER PLANTS↗

Structure-aware annotation of leucine-rich repeat domains

Protein domain annotation is typically done by predictive models such as HMMs trained on sequence motifs. However, sequence-based annotation methods are prone to error, particularly in calling domain boundaries and motifs within them. These methods are limited by a lack of structural information accessible to the model. With the advent of deep learning-based protein structure prediction, existing sequenced-based domain annotation methods can be improved by taking into account the geometry of protein structures. We develop dimensionality reduction methods to annotate repeat units of the Leucine Rich Repeat solenoid domain. The methods are able to correct mistakes made by existing machine learning-based annotation tools and enable the automated detection of hairpin loops and structural anomalies in the solenoid. The methods are applied to 127 predicted structures of LRR-containing intracellular innate immune proteins in the model plant Arabidopsis thaliana and validated against a benchmark dataset of 172 manually-annotated LRR domains.

Xu, Boyan↗

Bilayer Metasurfaces for Dual- and Broadband Optical Antireflection

Optical antireflection has long been pursued for a wide range of applications, but existing approaches encounter issues in the performance, bandwidth, and structure complexity, particularly in the long-wavelength infrared regime. Here we present the demonstration of bilayer metasurfaces that accomplish dual- and broadband optical antireflection in the terahertz and mid-infrared spectral ranges. Furthermore, by simply tailoring the structural geometry and dimensions, here we show that subwavelength metal/dielectric structures enable dramatic reduction of Fresnel reflection and significant enhancement of transmission at a substrate surface, operating either at two discrete narrow bands or over a broad bandwidth up to 28%. We also use a semianalytical interference model to interpret the obtained results, in which we find that the dispersion of the constituent structures plays a critical role in achieving the observed broadband optical antireflection.

36 MATERIALS SCIENCE↗

A method of order reduction for structural dynamics

This paper presents a new method of order reduction based on recent work of a similar nature applicable to system dynamics and control. This method provides a practical computational procedure for producing a condensed model which exactly preserves the slowest n1 modes (where n1 is the number of 'slow' eigenvalues) of the total n modes of the original model for almost any set of n1 degrees of freedom retained in the condensed model. The method can also be used to compute the eigensolutions corresponding to the n1 slowest modes of the original structural dynamics problem. The accuracy of the condensed model and the speed/accuracy performance of the eigensolver are compared with standard methods for a 90 DOF cantilevered plate.

Anderson, L. R.↗